Transformers是用于NLP开发的模型,由Hugging Face开发的一个library,和Hub进行了集成,在Hub上面,很多模型都是基于transformers开发的,这些models的功能有很多: NLP:文本分类,命名实体识别,问答,语言模型,摘要,翻译,文本生成 计算机视觉:文本分类,目标检测,分割 音频:语音识别,语音分类 多模态:表格问答,OCR,信息抽取,视频...
Hugging Face is a popular open-source platform for building and sharing state-of-the-art models in natural language processing. The Semantic Kernel API, on the other hand, is a powerful tool that allows developers to perform various NLP tasks, such as text classification and entity recognition,...
总结来看，Hugging Face 的 Model Hub 与 GitHub Models 均为开发者提供了前沿开源模型的快速体验平台。但是，GitHub 目前更多是瞄准科技大厂的开源基座模型，尚未将已在其平台开源的其他优质模型纳入考虑。反观 Hugging Face，从模型数量到覆盖的应用领域，都远胜于 GitHub。值得一提的是，为了进一步加速研究人员的工作...
【Running Hugging Face Models on Raspberry Pi】https:///www.youtube.com/watch?v=2rJCGyHQ_zM 在 Raspberry Pi 上运行拥抱面部模型。 û收藏 7 评论 ñ6 评论 o p 同时转发到我的微博 按热度 按时间 正在加载,请稍候... 互联网科技博主 超话主持人(网路冷眼技术分享超...
Learn how to fine-tune a natural language processing model with Hugging Face Transformers on a single node GPU.
Hugging Face Transformers models expect tokenized input, rather than the text in the downloaded data. To ensure compatibility with the base model, use anAutoTokenizerloaded from the base model. Hugging Facedatasetsallows you to directly apply the tokenizer consistently to both the training and testing...
This document presents various use cases of Hugging Face models from MindsDB. Spam Classifier Here is an example of a binary classification. The model determines whether a text string is spam or not. CREATE MODEL mindsdb.spam_classifier PREDICT PRED USING engine = 'huggingface', task = '...
hf-models 主要是提供 huggingface 热门模型镜像,方便国内开发者快速获取 概览仓库18472任务13Pull Requests1动态成员4 热门 flux1-dev-bnb-nf4 Mirror of https://huggingface.co/lllyasviel/flux1-dev-bnb-nf4 1 0 0 JanusFlow-1.3B Mirror of https://huggingface.co/deepseek-ai/JanusFlow-1.3B ...
) * feat(hugging_face): Add support for multiple models and dimensions see: alchaplinsky/hugging-face@bee85a4 * dimensions does not exist with hugging face * Add embeeding specs * fix: re-add default_dimensions * fix default_dimensions generation * Add vcrmain...
In this two-part blog series, we explore how to perform optimized training and inference of large language models from Hugging Face, at scale, on Azure